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Gabouer, Allison; Oghalai, John; Bortfeld, Heather – Discourse Processes: A Multidisciplinary Journal, 2020
In the current study we examine how hearing parents use multimodal cuing to establish joint attention with their hearing (n = 9) or deaf (n = 9) children during a free-play session. The deaf children were all candidates for cochlear implantation who had not yet been implanted, and each hearing child was age-matched to a deaf child. We coded…
Descriptors: Deafness, Hearing Impairments, Cues, Attention
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Bögels, Sara; Torreira, Francisco – Discourse Processes: A Multidisciplinary Journal, 2021
This study investigated the role of contextual and prosodic information in turn-end estimation by means of a button-press task. We presented participants with turns extracted from a corpus of telephone calls visually (i.e., in transcribed form, word-by-word) and auditorily, and asked them to anticipate turn ends by pressing a button. The…
Descriptors: Intonation, Suprasegmentals, Task Analysis, Visual Stimuli
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Gunraj, Danielle N.; Klin, Celia M. – Discourse Processes: A Multidisciplinary Journal, 2012
Despite the longstanding belief in an inner voice, there is surprisingly little known about the perceptual features of that voice during text processing. This article asked whether readers infer nonlinguistic phonological features, such as speech rate, associated with a character's speech. Previous evidence for this type of auditory imagery has…
Descriptors: Speech Communication, Silent Reading, Auditory Stimuli, Verbal Communication
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Lee, Mina; Roskos-Ewoldsen, Beverly; Roskos-Ewoldsen, David R. – Discourse Processes: A Multidisciplinary Journal, 2008
The Landscape Model of text comprehension was extended to the comprehension of audiovisual discourse from text and video TV news stories. Concepts from the story were coded for activation after each sequence, creating a matrix of activations that was reduced to a vector of the degree of total activation for each concept. In Study 1, the degree…
Descriptors: Television Viewing, Television, Correlation, Models